Integration Partner Data Quality

Bear IQ connects to a range of third-party systems — registration platforms, exhibit sales tools, and association management systems. The quality of data in Bear IQ is partly determined by the quality of those integrations. Not all platforms are built equally, and these differences have a direct impact on data alignment.

This article is about transparency: here’s how partner quality varies, what Bear Analytics does about it, and what it means for you.

How Integration Quality Varies

Every integration partner provides data access through an API. The design and reliability of that API determines what Bear IQ can access, how consistently it can access it, and how much additional work is needed to make the data usable.

API Robustness and Stability

Some partners maintain well-documented, stable APIs that deliver consistent data on every sync. Others have APIs that experience downtime, return inconsistent results, or change without notice.

A stable API partner means reliable data delivery and fewer alignment issues. A less stable partner may result in occasional sync failures, intermittent data gaps, or unexpected format changes that require Bear Analytics to update the integration.

Bear Analytics actively monitors integration health and addresses instability before it reaches your dashboards. But the root cause is the partner’s API quality, not Bear IQ.

Data Completeness

Some platforms expose rich, detailed data through their APIs — every field, every status, every timestamp. Others provide a limited subset of what’s available in the platform’s own interface.

When a partner’s API provides more detail, Bear IQ can offer finer segmentation and more accurate tuning. When the API is limited, Bear Analytics works within those constraints and may supplement with alternative data sources or manual processes where needed.

Fields that commonly vary by partner include: cancellation reasons, historical record changes (audit trail), line-item financial breakdowns, and attendee demographic fields.

Record Handling Practices

This is one of the most significant differences between partners, and it has a direct impact on data alignment.

Well-designed systems:

• Mark cancelled transactions with a status change, preserving the full record history so Bear IQ can accurately filter them

• Log record updates additively so changes can be tracked over time

• Use consistent, persistent unique identifiers so Bear IQ can reliably match records across syncs

Less disciplined systems:

• Hard-delete records rather than marking them cancelled. When a registration is deleted at the source, Bear IQ loses the ability to track that it ever existed — causing discrepancies that can’t be reconciled because the data is gone

• Allow users to overwrite existing records for new transactions instead of creating fresh ones, corrupting historical data

• Recycle or change unique identifiers between syncs, making record continuity difficult to maintain

Sync Frequency and Update Protocols

Some partners support frequent, incremental syncs — pulling only records that changed since the last sync. This is efficient and keeps data fresh.

Others require full data pulls every time, which takes longer and creates wider timing gaps. Some partners also have rate limits, maintenance windows, or batch-processing schedules that constrain when data can be synced, regardless of Bear IQ’s own refresh schedule.

How Bear Analytics Manages Partner Variability

Bear Analytics doesn’t simply accept whatever the integration delivers. Active work happens behind the scenes:

• Integration monitoring — every integration is monitored for sync health, data completeness, and anomalies

• Compensating logic — when a partner’s data practices create challenges (e.g., hard deletes, overwrites), Bear Analytics builds rules to detect and account for these behaviors where possible

• Partner advocacy — when API limitations or instability affect data quality, Bear Analytics engages with the partner to request improvements, expanded data access, or bug fixes

• Transparent communication — if a partner’s data quality is impacting your reporting in a way that can’t be fully mitigated, your Bear Analytics team will explain the impact and discuss options

What This Means for You

You may notice that data from some source systems aligns more closely with Bear IQ than data from others. This typically reflects the underlying quality difference between integration partners, not an issue with Bear IQ’s processing.

If you’re evaluating new event technology vendors — registration, exhibit sales, or AMS — Bear Analytics can provide perspective on which platforms tend to be stronger integration partners. We’ve worked with enough of them to know where the strengths and pain points are.

Continuous Improvement

The events technology ecosystem is always evolving. Partners update their APIs, add new features, and sometimes improve their data practices. Bear Analytics continuously evaluates and updates integrations to take advantage of these improvements — often without any action needed from you.

This is part of the ongoing value of having Bear Analytics manage the integration layer between your source systems and your analytics.